Front vehicle detecting method and front vehicle detecting apparatus

ABSTRACT

A method for detecting a front vehicle comprises: a moving light detecting step of detecting a front moving light area of an own vehicle in at least one image of a front scene of the own vehicle obtained at a time; a vehicle candidate generating step of extracting a light area pair from the detected front moving light area so that a front vehicle candidate is generated; and a vehicle candidate verifying step of verifying that the front vehicle candidate is the front vehicle in cases where the front vehicle candidate meets predetermined characteristics of a vehicle light.

BACKGROUND OF THE INVENTION

1. Field of the Invention

The present invention relates to a vehicle detecting method and avehicle detecting apparatus, and more particularly to a front vehicledetecting method and a front vehicle detecting apparatus.

2. Description of the Related Art

One of the major reasons for traffic accidents is nighttime driving,because the vision of a driver in the nighttime is worse than that inthe daytime. In the nighttime driving, it is possible to provide bettervision for the driver by a high-beam of the vehicle headlights. On theother hand, the high-beam may have an influence on a driver on theopposite side, and it may bring danger to the driver on the oppositeside. It may be rather inconvenient for the driver to switch frequentlyby hand between high-beam and low-beam.

U.S. Pat. No. 7,512,252B2 discloses a vehicle detecting system, in whicha long time exposure and a short time exposure are conductedrespectively by an onboard camera so as to obtain two images, andtaillights, headlights, and other lights (for example, signal lights orstreet lights) are identified by using image characteristics in the twoimages having different exposures.

The above patent (U.S. Pat. No. 7,512,252B2) relies on a condition thatin JAPAN traffic keeps to the left and an assumption that the headlightis located in the right side of the image and the taillight is locatedin the left side of the image; however, as for the practical reality ofroad conditions, the road is not always straight and the road may haveplural lanes, so that the assumption is not always correct. Furthermore,the above patent (U.S. Pat. No. 7,512,252B2) determines whether thelight comes from the vehicle or not by comparing the locationrelationship between a vanishing point and the detected light; however,the assumption is not always correct in the case of an uneven road (forexample, a slope). In addition, in the above patent (U.S. Pat. No.7,512,252B2), the taillight appears only in an image having a long timeexposure by controlling exposure intensity; however, the intensity ofthe light has relationships with both (1) a condition that the light isa headlight or taillight and (2) the distance between the light and theown vehicle. For example, the intensity of the taillight of the vehiclein the near distance may be higher and the light of the taillight of thevehicle in the near distance may be brighter than the headlight of thevehicle beyond. Therefore, the assumption is not always correct.

Furthermore, U.S. Pat. No. 7,429,825B2 discloses a vehicle light controlsystem, comprising: a rear vehicle information catching module forcatching the information of a vehicle behind the own vehicle; anovertaking forecasting module for forecasting whether the rear vehicleovertakes the own vehicle or not based on the information of the rearvehicle; a mode change condition determining module for determiningwhether a predetermined mode change condition is met or not based on theforecasted overtaking; and an automatic mode setting module for bringingout the automatic changeover between the high-beam and the low-beam incases where the predetermined mode change condition is met.

However, in the vehicle light control system of U.S. Pat. No.7,429,825B2, the detection based on the white line of the road (lane) inthe nighttime merely detects the rear vehicle in the same lane with theown vehicle, but cannot detect the front vehicle of the own vehicle.

Therefore, it is necessary to provide a method and an apparatus by whichthe front vehicle of the own vehicle can be detected in the nighttime.

SUMMARY OF THE INVENTION

The present invention is made in light of the above problems, and mayprovide a method and an apparatus for detecting the front vehicle of theown vehicle by detecting a moving light in front of the own vehicle anddetermining whether the moving light meets predetermined characteristicsof a vehicle light or not.

According to an aspect of the present invention, a method for detectingfront vehicle, comprises: a moving light detecting step of detecting afront moving light area of an own vehicle in at least one image of afront scene of the own vehicle obtained at a time; a vehicle candidategenerating step of extracting a light area pair from the detected frontmoving light area so that a front vehicle candidate is generated; and avehicle candidate verifying step of verifying that the front vehiclecandidate is the front vehicle in cases where the front vehiclecandidate meets predetermined characteristics of a vehicle light.

Preferably, in the front vehicle detecting method, the moving lightdetecting step comprises: a light area extracting step of extracting alight area from a first image of the at least one image; a distancecalculating step of calculating a distance between the extracted lightarea and the own vehicle; a light area matching step of matching theextracted light area with a light area of a first image of at least oneimage obtained at a previous time; and a moving light determining stepof determining the obtained light area as the front moving light area incases where the obtained light area meets predetermined characteristicsof a moving light area.

Preferably, the front vehicle detecting method, before the vehiclecandidate generating step, further comprises: a step of detecting avehicle layer in a first image of the at least one image; and a step ofeliminating a moving light area appearing above the vehicle layer.

Preferably, in the front vehicle detecting method, the vehicle candidategenerating step comprises: a light pair extracting step of constitutingthe light area pair by approximately symmetric light areas having asimilar speed in a first image of the at least one image; and a lightpair combining step of combining the light areas that constitute thelight area pair into one area so that the front vehicle candidate isobtained.

Preferably, the front vehicle detecting method, after the light pairextracting step, further comprises: a step of generating a straight lineacross each of the light area pairs, calculating the gradients of thestraight lines, and calculating the numbers of light crossed by thestraight lines; a step of detecting the straight line that crosses themost lights; and a step of removing the lights crossed by the straightline that crosses the most lights in cases where the gradient of thestraight line that crosses the most lights is within a predeterminedgradient range.

Preferably, the front vehicle detecting method further comprises: avehicle chasing step of matching a location of the front vehicledetermined in a first image of the at least one image to a location ofthe front vehicle determined in a first image of at least one imageobtained at a previous time so as to track the location of the frontvehicle.

According to another aspect of the present invention, an apparatus fordetecting a front vehicle, comprises: a moving light detecting unit fordetecting a front moving light area of an own vehicle in at least oneimage of a front scene of the own vehicle obtained at a time; a vehiclecandidate generating unit for extracting a light area pair from thedetected front moving light area so that a front vehicle candidate isgenerated; and a vehicle candidate verifying unit for verifying that thefront vehicle candidate is the front vehicle in cases where the frontvehicle candidate meets predetermined characteristics of a vehiclelight.

Preferably, in the front vehicle detecting apparatus, the moving lightdetecting unit comprises: a light area extracting unit for extracting alight area from a first image of the at least one image; a distancecalculating unit for calculating a distance between the extracted lightarea and the own vehicle; a light area matching unit for matching theextracted light area with a light area of a first image of at least oneimage obtained at a previous time; and a moving light determining unitfor determining the obtained light area as the front moving light areain cases where the obtained light area meets predeterminedcharacteristics of a moving light area.

Preferably, in the front vehicle detecting apparatus, the vehiclecandidate generating unit comprises: a light pair extracting unit forconstituting the light area pair by approximately symmetric light areashaving a similar speed in a first image of the at least one image; and alight pair combining unit for combining the light areas that constitutethe light area pair into one area so that the front vehicle candidate isobtained.

Preferably, the front vehicle detecting apparatus further comprises: avehicle chasing unit for matching a location of the front vehicledetermined in a first image of the at least one image to a location ofthe front vehicle determined in a first image of at least one imageobtained at a previous time so as to track the location of the frontvehicle.

According to the method and the apparatus for detecting the frontvehicle, the front vehicle of the own vehicle can be accurately detectedby detecting the moving light and verifying whether the detected movinglight meets the characteristics of the vehicle light or not.

BRIEF DESCRIPTION OF THE DRAWINGS

The above object and other objects, features, advantages and industrialimportance of the present invention will become more apparent from thefollowing detailed description when read in conjunction with theaccompanying drawings.

FIG. 1 is a flowchart illustrating the front vehicle detecting methodaccording to an embodiment of the present invention;

FIG. 2 is a flowchart illustrating the moving light area detectionaccording to the embodiment of the present invention;

FIG. 3 is a flowchart illustrating the front vehicle candidategeneration according to the embodiment of the present invention;

FIG. 4 is a flowchart illustrating the vehicle layer extractionaccording to the embodiment of the present invention;

FIG. 5 is a diagram illustrating the vehicle layer extraction accordingto the embodiment of the present invention;

FIG. 6 is a flowchart illustrating the reflection plate detectionaccording to the embodiment of the present invention;

FIG. 7 is a diagram illustrating the reflection plate removal accordingto the embodiment of the present invention;

FIG. 8 is a diagram illustrating the determination whether the lightarea is crossed by the straight line according to the embodiment of thepresent invention;

FIG. 9 is a diagram illustrating an application example of the frontvehicle detecting method according to the embodiment of the presentinvention;

FIG. 10 is a block diagram illustrating the front vehicle detectingapparatus according to the embodiment of the present invention;

FIG. 11 is a block diagram illustrating the moving light detecting unitaccording to the embodiment of the present invention;

FIG. 12 is a block diagram illustrating the vehicle candidate generatingunit according to the embodiment of the present invention;

FIG. 13 is a block diagram illustrating other component units that maybe included in the front vehicle detecting apparatus according to theembodiment of the present invention;

FIG. 14 is a diagram illustrating an application example of the frontvehicle detecting apparatus according to the embodiment of the presentinvention; and

FIG. 15 is a diagram illustrating a vehicle headlight control systemutilizing nighttime front vehicle detection.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

In the following, a front vehicle detecting method and apparatusaccording to an embodiment of the present invention are described withreference to the accompanying drawings.

First, FIG. 1 is a flowchart illustrating a method 100 for detecting thefront vehicle of an own vehicle according to the embodiment of thepresent invention.

The method 100 for detecting the front vehicle according to theembodiment of the present invention begins in step S101.

In step S110, a moving light area in front of the own vehicle isdetected through at least one image of a front scene of the own vehicleobtained at a time.

Next, in step S120, a light area pair is extracted from the detectedfront moving light area so that a front vehicle candidate is generated.

After that, in step S130, the front vehicle candidate is verified as thefront vehicle in cases where the front vehicle candidate meetspredetermined characteristics of a vehicle light.

As an example, in step S130, the front vehicle candidate is verified bya Support Vector Machine (SVM). In the preprocessing, the imagecharacteristics (such as length-width ratio, histogram, edgecharacteristics, and projection characteristics, etc.) are extracted soas to train a SVM classifier. In the process of the verification, thesame characteristics are extracted as the input of the SVM classifier,from each of the front vehicle candidates obtained in step S120. Afterthat, the SVM classifier outputs 1 or −1 to indicate whether the frontvehicle candidate is a vehicle light (vehicle) or not. For example, SVMoutputting 1 means the front vehicle candidate is the vehicle light(vehicle), while outputting −1 means the front vehicle candidate is notthe vehicle light (vehicle).

As another example, in step S130, the front vehicle candidate isverified by Principal Component Analysis (PCA). In the preprocessing, afew image blocks which include only the vehicle light are selected so asto train eigenvectors of the vehicle image space, and another set ofvehicle light images are projected to an eigenspace consisting of theeigenvectors so as to obtain projecting vector collection T. In theprocess of the verification, each of front vehicle candidates obtainedin step S120 is projected to the eigenspace obtained by training so asto obtain the projecting vectors. After that, the distances between theprojecting vectors and each of projecting vectors in the projectingvector collection T are calculated. If minimum distance is less than apredetermined threshold, the current front vehicle candidate isdetermined to be the detected front vehicle; otherwise, the currentfront vehicle candidate is regarded as noise light.

Finally, the method 100 for detecting the front vehicle according to theembodiment of the present invention finishes in step S199.

FIG. 2 is a flowchart illustrating the moving light area detection ofstep S110 in FIG. 1.

First, in step S1110, a light area in a first image of the at least oneimage is extracted.

Next, in the step S1120, a distance D_(t) between the extracted lightarea and the own vehicle is calculated.

It has been noted that a lot of other lights and vehicle light arephysically very similar, such as the light of buildings, street lightand light of a reflecting plate, etc. Because these lights are regardedas noise lights, the difficulty of vehicle light location detection in asingle image is increased.

Accordingly, preferably, in step S1120, the distance between theextracted light area and the own vehicle is calculated by using at leasttwo images, namely, at least two images having fixed parallax picked upby at least two webcams (such as a binocular webcam).

Alternatively, a single image may be picked up by a single webcam, andthe distance between the extracted light area and the own vehicle may bemeasured by other ways such as infrared distance measurement, etc.

After that, in step S1130, the extracted light area is matched to alight area of a first image of at least one image obtained at a previoustime.

As an example, in step S1130, the histogram of each of the extractedlight areas is calculated by the method of template matching, thenearest areas to each of the extracted light areas from a respondingimage obtained at a previous time are searched, histograms of each imageblock in the nearest areas are calculated, and histograms of theextracted light areas are compared with the calculated histograms ofeach image block. The calculation formula is defined as the followingformula (1).

${SD} = {\sum\limits_{i = 1}^{bins}\left( {{H_{t}\lbrack i\rbrack} - {H_{k,{t - 1}}\lbrack i\rbrack}} \right)^{2}}$

In formula (1), SD is the distance between the two histograms, H_(t)[i]is the i-th value of histograms of the light areas extracted from thecurrent image, H_(k,t-1) [i] is the i-th value of histograms of the k-thimage block of the nearest areas in the image obtained at the previoustime, and bins is the number of grey levels of histograms, such as 256.If the smallest SD value is less than a predetermined threshold, it isconsidered a successful matching between the extracted light area andthe image block (namely, light area) corresponding to the smallest SDvalue in the nearest areas.

Next, in step S1140, it is determined whether the extracted light areameets predetermined characteristics of a moving light area or not.

Finally, in step S1150, the extracted light area is determined to be thefront moving light area.

As an example, in step S1140, the moving speed V_(light) of theextracted light area is calculated by using the distance D_(t), thedistance D_(t-1) between light area matched at the previous time and theown vehicle, and the moving speed V_(t) of the own vehicle. Thecalculation formula is defined as the following formula (2).

V _(light)=(D _(t) −D _(t-1))/Δt+V _(t)

Furthermore, in step S1140, it is determined whether the moving speed ismore than a predetermined threshold. After that, in step S1150, thelight area there the moving speed is more than the predeterminedthreshold, is regarded as the front moving light area.

As another example, in step S1140, it may be determined whether the sizeof the extracted light area is less than the size of a correspondinglight area of a corresponding image obtained at the previous time ornot. After that, in step S1150, if the size of the extracted light areais less than the size of the corresponding light area of thecorresponding image obtained at the previous time, the extracted lightarea is regarded as the front moving light area.

As another example, in step S1140, it may be determined whether thedistance between the extracted light area and a vanishing point is lessthan the distance between a corresponding light area of a correspondingimage obtained at the previous time and the vanishing point or not.After that, in step S1150, if the distance between the extracted lightarea and the vanishing point is less than the distance between thecorresponding light area of the corresponding image obtained at theprevious time and the vanishing point, the extracted light area isregarded as the front moving light area and it is considered that themoving light area goes forward (namely, the same direction as the ownvehicle). In view of the fact that the vanishing point of the image iswell-known in the art, its description is omitted here.

Preferably, in step S1110, the first image (which is a grey level image,or is converted to a grey level image in advance) of the at least oneimage is converted to a binarized image, then the light area isextracted from the generated binarized image. However, the presentinvention is not limited to those steps described above, and there maybe no need to convert the first image of the at least one image to thebinarized image, but the light area may be extracted directly from thefirst image of the at least one image.

As an example, in step S1110, each pixel value of the grey level imageof the first image of the at least one image is compared with apredetermined threshold T_Binarization. If the grey level of the currentpixel is more than the threshold, set it to 255; otherwise, set thepixel value to 0. Thus, the corresponding binarizaed image is generated.After that, in the binarized image, the location and the size of all ofthe connect components (connect area) of the image are obtained byConnected Component Analysis (CCA), and the width and the height of eachconnect component is calculated. CC.width represents the width of theconnected component, and CC.height represents the height of theconnected component. T_CCWidth represents the threshold of width of theconnected component, T_CCHeight represents the threshold of height ofthe connected component, and T_CCAspect represents the threshold of theratio of width to height. If a connected component meets the followingcondition (formula (3)), it is regarded as a possible light area.

CC.width>T_CCWidth

CC.height>T_CCHeight

CC.width/CC.height<T_CCAspect

Furthermore, in view of the fact that the Connected Component Analysis(CCA) is well-known in the art, its description is omitted here.

It should be noted that the subsequent processing is done by using thefirst image, after the light area is extracted by using the binarizedimage of the first image.

Next, FIG. 3 is a flowchart illustrating the front vehicle candidategeneration of step S120 in FIG. 1.

First, in step S1210, in the first image, the light area pair isconstituted by approximately symmetric light areas having a similarspeed, after the front moving light area is detected.

Next, in step S1220, the light areas that constitute the light area pairare combined (merged) into one area so as to obtain the front vehiclecandidate.

In addition, preferably, if the two light areas overlap each other inthe vertical direction and the ratio of length to width of the boundingbox rectangle consisting of the two light areas is less than apredetermined threshold, the two light areas are combined into one area.

As mentioned above, a lot of lights are physically very similar tovehicle light, such as the light of buildings, street light and light ofa reflecting plate, etc. These lights are regarded as noise lights. Itis possible that a few non-truly moving light areas may also exist inthe moving light areas obtained in step S110, such as some of lights ofbuildings, some of street lights and some of lights of a reflectingplate, etc. Therefore, it is necessary to eliminate the non-truly movinglight areas from the obtained moving light areas.

In the present invention, a method of vehicle layer extraction and amethod of reflecting plate elimination are presented. In the method ofvehicle layer extraction, “vehicle layer” is detected from the image,and the detected lights (such as some of street lights and some oflights of buildings) above the vehicle layer are eliminated as thenoise; in the method of reflecting plate elimination, the “reflectingplate” is detected and eliminated from the image.

FIG. 4 is a flowchart illustrating the vehicle layer extraction.

In step S410, the vehicle layer is detected from the first image. Forexample, the first image is divided into several layers in thehorizontal direction from top to bottom, and the numbers of lights ineach layer are calculated. If the number of lights in the layer havingmost lights is more than a predetermined threshold, the layer is definedas the vehicle layer.

In step S420, the moving light area appearing above the vehicle layer iseliminated. For example, the lights appearing above the vehicle layerare eliminated as noise light. If the numbers of lights in all layersare less than the threshold, no vehicle layer is detected. FIG. 5illustrates the detection of the vehicle layer.

However, it should be noted that the vehicle layer detection is arequired step.

Next, FIG. 6 is a flowchart illustrating the reflection plate detection.

In step 610, in the first image, straight lines across each light areapair are generated, the gradients of the straight lines are calculated,and the numbers of lights crossed by the straight lines are calculated.

As an example, (a1, b1) and (a2, b2) respectively represent centralpoints of the two lights in the light area pair, and the gradient of thestraight line across the light area pair is calculated according to thefollowing formula (4),

k=(b2−b1)/(a2−a1)

and the coordinates (0, b) of the intersection between the straight lineand y axis is calculated according to the following formula (5).

b=b2−k×a2

Next, in step S620, the straight line across most lights is detected.Preferably, the straight line may be associated with the lights crossedby the straight line.

For example, suppose that the lights are represented by four points (asshown in FIG. 8), and (x₁, y₁), (x₂, y₂), (x₃, y₃), (x₄, y₄) representrespectively the coordinates of the four points. If the followingformula (one of the following two formulas (6) and (7)) is met, it isjudged that the straight line crosses the light.

(y ₁ −kx ₁ −b)×(y ₃ −kx ₃ −b)<0

(y ₂ −kx ₂ −b)×(y ₄ −kx ₄ −b)<0

Next, in steps S630 and S640, if the gradient of the straight lineacross most lines is within a predetermined gradient range, lightscrossed by the straight line across most lights are removed.

As an example, if the gradient k of the straight line is within apredetermined gradient range, such as k>0.5 or k<−0.5, lights crossed bythe straight line are removed as the noise light.

As shown in FIG. 7, lights on the straight line in which light pair 9and 10 are located, namely, lights 9, 10, 11, 14 and 16 are removed.

Furthermore, the front vehicle detecting method according to theembodiment of the present invention preferably further comprises avehicle chasing step. In the vehicle chasing step, the vehicle locationof the first image of the at least one image obtained at the currenttime is calculated, based on the vehicle location detected from thefirst image of the at least one image obtained at the previous time.

As an example, a template matching method is used in the chasing step.In other words, in the current image, the histogram of each image blockis calculated in the neighborhood thereof based on the vehicle locationdetected from the image obtained at the previous time, and thecalculated histogram is compared with the histogram of the vehicle imageblock detected from the image obtained at the previous time. Thecalculating formula (8) is as follows.

${SD} = {\sum\limits_{i = 1}^{bins}\left( {{H_{k,t}\lbrack i\rbrack} - {H_{t - 1}\lbrack i\rbrack}} \right)^{2}}$

In formula (8), SD is the distance between the two histograms, H_(k,t)[i] is the i-th value of histogram of the k-th neighborhood image blockin the current image, H_(t-1) [i] is the i-th value of histogram of thevehicle image block extracted from the image obtained at the previoustime, and bins is the number of grey level of histograms, such as 256.The area having a smallest SD value is the forecasted location of thevehicle. If the smallest SD value is still more than a predeterminedthreshold, it is considered that the vehicle detected from the imageobtained at the previous time has vanished in the current image so thatno matching result exists in the current image.

As another example, a Kalman filter method may be used in the chasingstep, wherein, the speed of the detected vehicle is estimated, and themost probable location that the vehicle detected from the image obtainedat the previous time appears in the current image is estimated; so that,a small search scope of the current image is determined and the vehiclelocation is forecasted in this scope by the template matching method.

Next, FIG. 9 is a diagram illustrating an application example of thefront vehicle detecting method.

It is possible to detect automatically the front vehicle of the ownvehicle, by using the front vehicle detecting method according to theembodiment of the present invention. For the own vehicle, it is capableof switching automatically high-beam and low-beam (such as long-distancelight and short-distance light) of the headlight of the vehicle based onthe detection result.

As an application example, if there is no vehicle in the range of frontvision, high-beam (long-distance light) is turned on automatically; ifthe front vehicle is detected, the headlight is switched automaticallyto the status of low-beam (short distance light). According to thisapplication, it is capable of providing better front vision for thedriver of the own vehicle, and maximally reducing the interference toother drivers.

As another application example, the own vehicle may controlautomatically the area of light irradiation, use low-beam only in thearea that the vehicle is detected and use high-beam in other areas (asshown in FIG. 9).

As described above, it is possible to detect automatically the frontvehicle of the own vehicle by using the front vehicle detecting methodaccording to the embodiment of the present invention. In the ownvehicle, it is possible to perform Auto Cruise Control (ACC) or ForwardCollision Warning (FCW), etc., based on the detected front vehicle.

Next, FIG. 10 is a block diagram illustrating the front vehicledetecting apparatus 1000 according to the embodiment of the presentinvention.

The front vehicle detecting apparatus 1000 according to the embodimentof the present invention receives an image of the front vision of theown vehicle picked up by at least one webcam, and processes at least onereceived image so as to detect the front vehicle of the own vehicle.

Preferably, the at least one webcam may be at least two webcams such asa binocular webcam. The binocular webcam may be installed in theposition near the back mirror of the vehicle so as to capture the imageof the front scene of the own vehicle.

The front vehicle detecting apparatus 1000 comprises a moving lightdetecting unit 1010, a vehicle candidate generating unit 1020, and avehicle candidate verifying unit 1030.

The moving light detecting unit 1010 detects the front moving light areaof the own vehicle through at least one image of the front scene of theown vehicle obtained at a time.

The vehicle candidate generating unit 1020 extracts the light area pairfrom the detected front moving light area so that the front vehiclecandidate is generated.

The vehicle candidate verifying unit 1030 verifies that the frontvehicle candidate is the front vehicle in cases where the front vehiclecandidate meets predetermined characteristics of a vehicle light.

As an example, the vehicle candidate verifying unit 1030 may verify thefront vehicle candidate by a Support Vector Machine (SVM). In the SVMclassifier, the image characteristics (such as length-width ratio,histogram, edge characteristics, and projection characteristics, etc.)have been stored (trained). The vehicle candidate verifying unit 1030receives each of the obtained front vehicle candidates, extracts theabove characteristics from the front vehicle candidates, and inputs theextracted characteristics into the SVM classifier of the vehiclecandidate verifying unit 1030. After that, the SVM classifier outputs 1or −1 to determine whether the front vehicle candidate is a vehiclelight (vehicle) or not.

As another example, the vehicle candidate verifying unit 1030 may verifythe front vehicle candidate by Principal Component Analysis (PCA). Inthe PCA, eigenvectors of the vehicle image space and the eigenspaceconsisting of the eigenvectors have been stored (trained), and there isanother set of vehicle light images in the projecting vector collectionT of the eigenspace. The vehicle candidate verifying unit 1030 receivesthe obtained each of front vehicle candidates, the PCA of the vehiclecandidate verifying unit 1030 projects the front vehicle candidates tothe eigenspace so as to obtain the projecting vectors and calculates thedistances between the projecting vectors and each of projecting vectorsin the projecting vector collection T. If minimum distance is less thana predetermined threshold, the vehicle candidate verifying unit 1030verifies the front vehicle candidate as the detected front vehicle.

FIG. 11 is a block diagram illustrating the moving light detecting unit1010 according to the embodiment of the present invention.

The moving light detecting unit 1010 comprises a light area extractingunit 1011, a distance calculating unit 1012, a light area matching unit1013, and a moving light determining unit 1014.

The light area extracting unit 1011 extracts a light area through afirst image of the at least one image.

The distance calculating unit 1012 calculates the distance D_(t) betweenthe extracted light area and the vehicle.

The light area matching unit 1013 performs the matching between theextracted light area and a light area of a first image of at least oneimage obtained at a previous time.

As an example, the light area matching unit 1013 compares histograms ofeach of the extracted light areas with histograms of each image block inthe nearest areas of the corresponding image obtained at a previous timeso as to determine the smallest SD value according to the above formula(1), by the method of template matching. If the smallest SD value isless than a predetermined threshold, it is considered a successful matchbetween the extracted light area and the image block (namely, lightarea) corresponding to the smallest SD value in the nearest areas.

The moving light determining unit 1014 determines the extracted lightarea as the front moving light area in cases where the extracted lightarea meets predetermined characteristics of the moving light area.

As an example, the moving light determining unit 1014 calculates themoving speed V_(light) of the extracted light area according to theabove formula (2), by using the distance D_(t), the distance D_(t-1)between light area matched at the previous time and the own vehicle, andthe moving speed V_(t) of the own vehicle. And then, the moving lightdetermining unit 1014 determines whether the moving speed is more than apredetermined threshold, and determines the light area that the movingspeed is more than the predetermined threshold as the front moving lightarea.

As another example, the moving light determining unit 1014 may determinewhether the size of the extracted light area is less than the size of acorresponding light area of a corresponding image obtained at theprevious time or not. And then, the moving light determining unit 1014determines the extracted light area as the front moving light area, ifthe size of the extracted light area is less than the size of thecorresponding light area of the corresponding image obtained at theprevious time.

As another example, the moving light determining unit 1014 may determinewhether the distance between the extracted light area and a vanishingpoint is less than the distance between a corresponding light area of acorresponding image obtained at the previous time and the vanishingpoint or not. And then, the moving light determining unit 1014determines the extracted light area as the front moving light area andconsiders that the moving light area goes forward (namely, the samedirection with the own vehicle), if the distance between the extractedlight area and the vanishing point is less than the distance between thecorresponding light area of the corresponding image obtained at theprevious time and the vanishing point.

Preferably, the moving light detecting unit 1010 according to theembodiment of the present invention also comprises a binarization unit(not shown in the drawings). The binarization unit converts the firstimage (it is a grey level image, or it is converted to a grey levelimage in advance) of the at least one image to a binarized image. Inthis case, the light area extracting unit 1011 extracts the light areafrom the generated binarized image. However, it should be noted that thebinarization unit is a required component of the front vehicle detectingapparatus 1000 according to the embodiment of the present invention.

The binarization unit compares each pixel value of the grey level imageof the first image of the at least one image with a predeterminedthreshold T_Binarization, and sets the grey level of the current pixelto 255 if the grey level of the current pixel is more than thethreshold, otherwise sets the pixel value to 0; thus, the correspondingbinarized image is generated.

In this case, as an example, the light area extracting unit 1011 obtainsthe location and the size of all of the connect components (connectarea) of the image by Connected Component Analysis (CCA), calculates thewidth and the height of each connect component, and determines theconnect component as a possible light area if the connect componentmeets the above condition (formula (3)).

FIG. 12 is a block diagram illustrating the vehicle candidate generatingunit 1020 according to the embodiment of the present invention.

The vehicle candidate generating unit 1020 comprises a light pairextracting unit 1021 and a light pair combining unit 1022.

The light pair extracting unit 1021 constitutes the light area pair byapproximate symmetric light areas having a similar speed in a firstimage of the at least one image.

The light pair combining unit 1022 combines (merges) the light areasthat constitute the light area pair into one area so as to obtain thefront vehicle candidate. In addition, preferably, if the two light areasoverlap each other in the vertical direction and the ratio of length towidth of the bounding box rectangle consisting of the two light areas isless than a predetermined threshold, the light pair combining unit 1022combines the two light areas into one area.

Next, FIG. 13 is a block diagram illustrating other component units thatmay be included in the front vehicle detecting apparatus 1000 accordingto the embodiment of the present invention.

The front vehicle detecting apparatus 1000 according to the embodimentof the present invention may also comprise a vehicle layer extractingunit 1040, a reflection plate extracting unit 1050 and a vehicle chasingunit 1060.

The vehicle layer extracting unit 1040 detects the vehicle layer fromthe first image of the at least one image. For example, the first imageis divided into several layers in the horizontal direction from top tobottom, and the numbers of lights in each layer are calculated. If thenumber of lights in the layer having most lights is more than apredetermined threshold, the layer is defined as the vehicle layer.After that, the vehicle layer extracting unit 1040 eliminates the movinglight area appearing above the vehicle layer. For example, the lights(such as lights of buildings and street lights) appearing above thevehicle layer are eliminated as noise light. If the numbers of lights inall layers are less than the threshold, the vehicle layer extractingunit 1040 determines that no vehicle layer is detected and does noteliminate any lights accordingly.

The reflection plate extracting unit 1050 preferably comprises astraight line generating unit, a reflection plate straight linedetecting unit and a reflection plate removing unit.

In the first image, the straight line generating unit generates straightlines across each light area pair extracted by the light pair extractingunit 1021, and calculates the numbers of lights crossed by the straightlines based on the above formulas (4) and (5).

The reflection plate straight line detecting unit detects the straightline across most lights.

The reflection plate removing unit determines whether the gradient ofthe straight line detected by the reflection plate straight linedetecting unit is within a predetermined gradient range, and removeslights crossed by the straight line across most lights if the gradientis within a predetermined gradient range.

As an example, if the gradient k of the straight line is within apredetermined gradient range, such as k>0.5 or k<−0.5, The reflectionplate removing unit removes lights crossed by the straight line as thenoise light.

The vehicle chasing unit 1060 calculates the vehicle location of thefirst image of the at least one image obtained at the current time,based on the vehicle location detected from the first image of the atleast one image obtained at the previous time.

As an example, the vehicle chasing unit 1060 uses a template matchingmethod, namely, in the current image, calculates the histogram of eachimage block in the neighborhood thereof based on the vehicle locationdetected from the image obtained at the previous time, and compares thecalculated histogram with the histogram of the vehicle image blockdetected from the image obtained at the previous time based on the aboveformula (8). The area having a smallest SD value is the forecastedlocation of the vehicle. If the smallest SD value is still more than apredetermined threshold, it is considered that the vehicle detected fromthe image obtained at the previous time has vanished in the currentimage.

As another example, the vehicle chasing unit 1060 may use a Kalmanfilter method, namely, the speed of the detected vehicle is estimated,and estimates the most probable location that the vehicle detected fromthe image obtained at the previous time appears in the current image;thereby, a small search scope of the current image is determined and thevehicle location is forecasted to be in this scope by the templatematching method.

FIG. 14 is a diagram illustrating an application example of the frontvehicle detecting apparatus 1000 according to the embodiment of thepresent invention.

As shown in FIG. 15, the front vehicle detecting apparatus 1000according to the embodiment of the present invention may be used with aheadlight control unit 2010 so as to form a vehicle headlight controlsystem 100.

The vehicle headlight control system 100 comprises a binocular webcam101, a front vehicle detecting apparatus 102, a headlight control module103 (such as the headlight control unit 2010), headlights 104 and aspeed sensor 105.

The binocular webcam 101 is located in the position of the back mirrorof the vehicle. The front vehicle detecting apparatus 102 consists ofthe front vehicle detecting apparatus 1000 according to the embodimentof the present invention.

The headlight control module 103 is able to receive the detection resultof the front vehicle from the front vehicle detecting apparatus 102 andswitch automatically high-beam and low-beam (such as long-distance lightand short-distance light) based on the detection result.

For example, if there is no vehicle in the range of front vision, theheadlight control module 103 turns on high-beam (long-distance light)automatically; if the front vehicle is detected, the headlight controlmodule 103 switches the headlight to the status of low-beam (shortdistance light) automatically. According to this application, theembodiment is capable of providing a better front vision for the driverof the own vehicle, and maximally reducing the interference to otherdrivers.

As another example, the headlight control module 103 may controlautomatically the area of light irradiation, use low-beam only in thearea that the vehicle is detected and use high-beam in other areas (asshown in FIG. 9).

Furthermore, the front vehicle detecting apparatus 1000 according to theembodiment of the present invention may be used with an automatic speedcontrol unit 2020 so as to form an automatic speed control system.

Furthermore, the front vehicle detecting apparatus 1000 according to theembodiment of the present invention may be used with a forward collisionwarning unit 2030 so as to form a forward collision warning system.

The front vehicle detecting method and apparatus are not limited to theabove application.

According to the front vehicle detecting method and apparatus of theembodiment of the present invention, the moving speed of lights isestimated based on the images obtained at two different time, the movinglights are detected based on the estimated moving speed, and the “noiselights” are also removed based on the characteristics of the vehiclelight, so that the front vehicle of the own vehicle is accuratelydetected.

It should be noted that the front vehicle detecting method and apparatusdescribed above may be implemented by various ways such as hardware,software, firmware, exclusive processor, or a combination of those.

It also should be noted that some of system components and methods shownin the drawings may be preferably implemented by software, so that theactual connection among these system components and processingfunctional block can be different based on the programming method of thepresent invention. The implementation and the configuration for thepresent invention are well-known in the art.

The present invention is not limited to the specifically disclosedembodiments, and variations and modifications may be made withoutdeparting from the scope of the present invention.

The present application is based on Chinese Priority Application No.201110297126.6 filed on Sep. 30, 2011, the entire contents of which arehereby incorporated herein by reference.

What is claimed is:
 1. A method for detecting a front vehicle,comprising: a moving light detecting step of detecting a front movinglight area of an own vehicle in at least one image of a front scene ofthe own vehicle obtained at a time; a vehicle candidate generating stepof extracting a light area pair from the detected front moving lightarea so that a front vehicle candidate is generated; and a vehiclecandidate verifying step of verifying that the front vehicle candidateis the front vehicle in cases where the front vehicle candidate meetspredetermined characteristics of a vehicle light.
 2. The methodaccording to claim 1, wherein the moving light detecting step comprises:a light area extracting step of extracting a light area from a firstimage of the at least one image; a distance calculating step ofcalculating a distance between the extracted light area and the ownvehicle; a light area matching step of matching the extracted light areawith a light area of a first image of at least one image obtained at aprevious time; and a moving light determining step of determining theobtained light area as the front moving light area in cases where theobtained light area meets predetermined characteristics of a movinglight area.
 3. The method according to claim 1, before the vehiclecandidate generating step, further comprising: a step of detecting avehicle layer from a first image of the at least one image; and a stepof eliminating a moving light area appearing above the vehicle layer. 4.The method according to claim 1, wherein the vehicle candidategenerating step comprises: a light pair extracting step of constitutingthe light area pair by approximately symmetric light areas having asimilar speed in a first image of the at least one image; and a lightpair combining step of combining the light areas that constitute thelight area pair into one area so that the front vehicle candidate isobtained.
 5. The method according to claim 4, after the light pairextracting step, further comprising: a step of generating a straightline across each of the light area pairs, calculating the gradients ofthe straight lines, and calculating the numbers of lights crossed by thestraight lines; a step of detecting the straight line that crosses mostlights; and a step of removing the lights crossed by the straight linethat crosses the most lights in cases where the gradient of the straightline that crosses the most lights is within a predetermined gradientrange.
 6. The method according to claim 1, further comprising: a vehiclechasing step of matching a location of the front vehicle determined in afirst image of the at least one image to a location of the front vehicledetermined in a first image of at least one image obtained at a previoustime so as to track the location of the front vehicle.
 7. An apparatusfor detecting a front vehicle, comprising: a moving light detecting unitfor detecting a front moving light area of an own vehicle in at leastone image of a front scene of the own vehicle obtained at a time; avehicle candidate generating unit for extracting a light area pair fromthe detected front moving light area so that a front vehicle candidateis generated; and a vehicle candidate verifying unit for verifying thatthe front vehicle candidate is the front vehicle in cases where thefront vehicle candidate meets predetermined characteristics of a vehiclelight.
 8. The apparatus according to claim 7, wherein the moving lightdetecting unit comprises: a light area extracting unit for extracting alight area from a first image of the at least one image; a distancecalculating unit for calculating a distance between the extracted lightarea and the own vehicle; a light area matching unit for matching theextracted light area with a light area of a first image of at least oneimage obtained at a previous time; and a moving light determining unitfor determining the obtained light area as the front moving light areain cases where the obtained light area meets predeterminedcharacteristics of a moving light area.
 9. The apparatus according toclaim 7, wherein the vehicle candidate generating unit comprises: alight pair extracting unit for constituting the light area pair byapproximately symmetric light areas having a similar speed in a firstimage of the at least one image; and a light pair combining unit forcombining the light areas that constitute the light area pair into onearea so that the front vehicle candidate is obtained.
 10. The apparatusaccording to claim 7, further comprising: a vehicle chasing unit formatching a location of the front vehicle determined in a first image ofthe at least one image to a location of the front vehicle determined ina first image of at least one image obtained at a previous time so as totrack the location of the front vehicle.